Harvesting Solar Energy for Green Buildings Through Plastic Optical-Fibre Daylighting Systems: A Systematic Review and Meta-Analysis.

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Title: Harvesting Solar Energy for Green Buildings Through Plastic Optical-Fibre Daylighting Systems: A Systematic Review and Meta-Analysis.
Authors: Tariq, Raheel1 (AUTHOR), Philbin, Simon P.1 (AUTHOR) s.philbin@kingston.ac.uk, Djaid, Nadia Touileb1 (AUTHOR), Munisami, Kevin J.1 (AUTHOR)
Source: Energies (19961073). Apr2026, Vol. 19 Issue 8, p1857. 55p.
Subject Terms: *Plastic optical fibers, *Daylighting, *Sustainable buildings, *Solar energy, *Evidence synthesis
Abstract: Optical-fibre daylighting systems (OFDS) harvest solar energy as a renewable lighting resource by delivering sunlight deep into green buildings. This emerging technology for sustainable infrastructure reduces electric-lighting demand; however, reported performance is difficult to compare across heterogeneous designs, metrics, and validation practices. Therefore, a PRISMA 2020–reported systematic literature review (SLR) of OFDS studies from three databases (Google Scholar, Scopus, and Web of Science; 2000–2025) was conducted, synthesising primary research that quantifies system- or component-level performance, with a focus on (i) plastic optical fibre (POF) transmission characteristics; and (ii) POF-based illuminance model validation. After de-duplication and screening, 106 primary studies were included, and two meta-analyses were performed where data were harmonised from 29 studies in total. Across reported POF configurations, attenuation ranged from 150 to 800 dB/km with a pooled mean of 332.8 dB/km, corresponding to a mean 1 m transmission of 92.7% and median design length scales of ∼3.7 m for 80% transmission and ∼11.6 m to half-power. Across illuminance validation datasets, models showed high linear agreement with experimental measurements (coefficient of determination ( R 2 ) = 0.99; slope = 0.99) but typically underpredicted illuminance (geometric mean ratio = 1.16; mean absolute error (MAE) = 27.3 lux; mean absolute percentage error (MAPE) = 17.6%). These findings underscore the need for a standardised evaluation framework, including consistent metric definitions, robust uncertainty reporting, and reusable validation datasets to enable variance-weighted synthesis, while also identifying short-run POF routing as a key lever for improving system efficiency. In addition to providing the OFDS research agenda, this study serves as a roadmap for the industrial development of daylighting systems for green buildings based on harvesting solar energy, with its novelty lying in the PRISMA-guided evidence synthesis and quantitative meta-analytic consolidation of POF transmission and illuminance-validation performance. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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  Data: Harvesting Solar Energy for Green Buildings Through Plastic Optical-Fibre Daylighting Systems: A Systematic Review and Meta-Analysis.
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Apr2026, Vol. 19 Issue 8, p1857. 55p.
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  Data: *<searchLink fieldCode="DE" term="%22Plastic+optical+fibers%22">Plastic optical fibers</searchLink><br />*<searchLink fieldCode="DE" term="%22Daylighting%22">Daylighting</searchLink><br />*<searchLink fieldCode="DE" term="%22Sustainable+buildings%22">Sustainable buildings</searchLink><br />*<searchLink fieldCode="DE" term="%22Solar+energy%22">Solar energy</searchLink><br />*<searchLink fieldCode="DE" term="%22Evidence+synthesis%22">Evidence synthesis</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Optical-fibre daylighting systems (OFDS) harvest solar energy as a renewable lighting resource by delivering sunlight deep into green buildings. This emerging technology for sustainable infrastructure reduces electric-lighting demand; however, reported performance is difficult to compare across heterogeneous designs, metrics, and validation practices. Therefore, a PRISMA 2020–reported systematic literature review (SLR) of OFDS studies from three databases (Google Scholar, Scopus, and Web of Science; 2000–2025) was conducted, synthesising primary research that quantifies system- or component-level performance, with a focus on (i) plastic optical fibre (POF) transmission characteristics; and (ii) POF-based illuminance model validation. After de-duplication and screening, 106 primary studies were included, and two meta-analyses were performed where data were harmonised from 29 studies in total. Across reported POF configurations, attenuation ranged from 150 to 800 dB/km with a pooled mean of 332.8 dB/km, corresponding to a mean 1 m transmission of 92.7% and median design length scales of ∼3.7 m for 80% transmission and ∼11.6 m to half-power. Across illuminance validation datasets, models showed high linear agreement with experimental measurements (coefficient of determination ( R 2 ) = 0.99; slope = 0.99) but typically underpredicted illuminance (geometric mean ratio = 1.16; mean absolute error (MAE) = 27.3 lux; mean absolute percentage error (MAPE) = 17.6%). These findings underscore the need for a standardised evaluation framework, including consistent metric definitions, robust uncertainty reporting, and reusable validation datasets to enable variance-weighted synthesis, while also identifying short-run POF routing as a key lever for improving system efficiency. In addition to providing the OFDS research agenda, this study serves as a roadmap for the industrial development of daylighting systems for green buildings based on harvesting solar energy, with its novelty lying in the PRISMA-guided evidence synthesis and quantitative meta-analytic consolidation of POF transmission and illuminance-validation performance. [ABSTRACT FROM AUTHOR]
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        Value: 10.3390/en19081857
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        Text: English
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        Type: general
      – SubjectFull: Daylighting
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      – SubjectFull: Sustainable buildings
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      – TitleFull: Harvesting Solar Energy for Green Buildings Through Plastic Optical-Fibre Daylighting Systems: A Systematic Review and Meta-Analysis.
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              Text: Apr2026
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              Y: 2026
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